Lte cell level layer management auto optimization

ABSTRACT

Systems and methods are provided to administer a wireless telecommunication network (WTN) having a plurality of cell sites. Network data is received from a data source for a subject cell site. A baseline performance of the subject cell site is determined. Parameters to optimize for the subject cell site based on the baseline performance are identified. Load balancing is performed on the subject cell site by comparing a normalized user equipment (UE) downlink (DL) throughput at a first cellular frequency band to a second cellular frequency band. A cellular coverage of the subject cell site is adjusted based on a voice over LTE (VoLTE) drop call rate for a predetermined time period and a normalized UE DLL throughput. A layer management is performed on the subject cell site.

BACKGROUND

Wireless telecommunication networks have evolved into complex systemsthat include various hardware that is often controlled with complexsoftware via a central station. Initial implementations of such wirelesscommunications, for example in the form of cellular telephone networks,supported circuit switched voice communication services. The carriersdeveloped short message service (SMS) technology to provide text and/ore-mail communications via the wireless communication networks. As thewireless communication networks have evolved to provide greaterbandwidth and packet based services, the wireless industry has developeda variety of data services, such as email, web browsing, as well as avariety of services using multimedia message service (MMS) technology.To accommodate the increasing demand of such wireless services, largescale wireless telecommunication networks often include an increasingnumber of cell sites, sometimes referred to as base stations, which areused to service mobile devices in various locations.

To effectively manage these wireless telecommunication networks,administrators track various key performance indicators (KPI's) for eachcell site. To administer the increasing number of cell sites, these cellsites are adjusted to have substantially similar configurations. Thus,cell sites are typically configured using a network-wide optimizationthat configures each cell site using substantially similar parameters.Such holistic approach for the entire network may be time efficient, butit often leaves individual cell sites to operate under non optimalconditions. While individual optimization of each cell site may bepossible, it is generally avoided due to high administrative cost.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is described with reference to the accompanyingfigures, in which the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical items.

FIG. 1 is an example architecture for implementing a wireless networksystem configured to optimize cell sites.

FIG. 2 is a block diagram of an illustrative controller configured tooptimize network performance of cell sites.

FIG. 3 illustrates an example schematic diagram of a computingarchitecture that can be used to perform automatic optimizing a cellindividually and in clusters.

FIGS. 4 and 5 illustrate flow diagrams of example processes to optimizethe performance of a wireless telecommunication network.

FIGS. 6A to 6D provide a summary of relevant KPI's and example solutionsfor various corrections to be performed onto individual cell sites.

DETAILED DESCRIPTION Overview

The techniques and systems described herein are directed, in part, tooptimizing network performance by optimizing the performance ofindividual cell sites and/or a cluster of individual cell sites of awireless telecommunication network and then optimizing each cell site(or cluster of cell sites), thereby optimizing performance of a networkas a whole. The cell sites may be base stations, radio accesspoints/networks, sites and/or other hardware that directly or indirectlyexchanges communications with user devices such as mobiletelecommunication devices (e.g., user handsets, user hardware, etc.,)collectively referred to herein as user equipment (UE). By optimizingeach cell cite individually, the performance of the individual cell sitecan be improved, thereby better serving the subscribers and providingmore efficiency to the wireless network provider. In some scenarios,cell sites that are exhibiting similar KPI values may be groupedtogether, such group being referred to herein as a cell cluster, whichcan be optimized together.

By virtue of optimizing each cell site individually or in clustersexhibiting common performance issues, a wireless service provider mayimprove network performance. In addition, the optimization of each cellsite individually or by way of a cluster may provide significant serviceimprovements (e.g., fewer dropped calls, more available bandwidth,etc.,) than an optimization that is applied across the entire network oran optimization that is based on geographic locations (e.g., optimizingcell sites for a city, a rural area, etc.) The techniques and systemsdescribed herein may be implemented in a number of ways. Exampleimplementations are provided below with reference to the followingfigures.

Illustrative Environment

FIG. 1 is an example architecture for implementing a wireless networksystem configured to optimize cell sites. Cell sites 102(1) to 102(N)may be optimized by a central controller 110 individually or byintelligent clusters that have common key performance indicators (KPI)values. The wireless telecommunication network 100 may include aplurality of hardware, software, and other infrastructure componentsthat may be typical of a large wireless telecommunications provider. Thecell sites 102(1) to 102(N) are associated with a radio access networks(RANs) 104(1) to 104(N) used for mobile communications. The cell sites102(1) to 102(N) may be located across different geographic areas tofacilitate providing network access and connectivity to users in theircorresponding geographic area. The cell sites 102(1) to 102(N) may bebase stations, or other network end points (or possibly intermediarypoints) that exchange communications with user devices, such as mobiletelecommunication devices, computing devices, or other devices that havewireless connectivity. The RANs 104 may be in communication with a corenetwork 108 directly or through one or more intermediaries 106,depending on the size and complexity of the wireless telecommunicationnetwork 100.

In accordance with one or more embodiments, the wirelesstelecommunication network 100 may conform to Universal MobileTelecommunications System (UMTS) technologies that employ UMTSTerrestrial Radio Access Network (UTRAN). In some instances, the UTRANmay share a several components like a Circuit Switch (CS) and a PacketSwitch (PS) core network with a GSM EDGE Radio Access Network (GERAN)(Global System for Mobile Communications (GSM), Enhanced Data rates forGSM Evolution (EDGE)). In various instances, a 4G long term evolution(4G/LTE) network that comprises Evolved UMTS Terrestrial Radio AccessNetwork (EUTRAN) may be employed to transmit data for thetelecommunications networks, besides UMTS or GSM. Thus, EUTRAN, UTRANand GERAN networks (and other possible RANs) may coexist to processtelecommunications traffic.

In some instances, communications may be handed off between EUTRAN,UTRAN and GERAN networks (or other networks) and still maintain acommunication with a common core network, such as when a UE leaves arange of access (zone) of a EUTRAN and enters a range of access of aUTRAN or GERAN. Handoffs may also occur between different types ofhardware (e.g., different manufacturers, versions, etc.,) for a samenetwork type (e.g., EUTRAN, UTRAN, GERAN, etc.). For discussionpurposes, it will be assumed that the architecture of FIG. 1 representsa 4G/LTE network that includes one or more evolved Node B's (eNodeB's),represented herein by cell sites 102(1) to 102(N), which provide aninterface between a UE, such as a wireless handheld device that isconfigured to communicate over the radio access network 104(1) to 104(N)and the core network 108. Each eNodeB couples with the core network 108via the mobility management entity (MME), represented by theintermediary layer 106, which is a control-node.

In accordance with one or more embodiments, other types of networks,RANs, and/or components (hardware and/or software) may be employed thatenable telecommunications devices to communicate with the core network108 to facilitate activities such as voice calling, messaging, emailing,accessing the Internet, or other types of data communications. Forexample, the wireless telecommunication network 100 may be, at least inpart, a Wi-Fi based network, a Bluetooth network, or other type ofwireless network.

The wireless telecommunication network 100 may include a centralcontroller 110 to manage network performance optimizations for each cellcite and/or cell site clusters based on predetermined common KPI values.The central controller 110 may be in communication with one or more ofthe various components of the wireless telecommunication network 100,such as the core network 108, the one or more intermediaries 106, theRANs 104(1) to 104(N), and/or the cell sites 102(1) to 102(N).

In one embodiment, the wireless telecommunication network 100 includes adata server 112 that is configured to provide information related to theperformance of each cell site individually, clusters of cell sites, orover the entire network. Such information may include, for each cellsite, a baseline information of KPI's, historical information regardingthe KPI's, trend information of the KPI's, etc. In some embodiments, thedata server 112 provides some of the aforementioned information oradditional performance information to the central controller 110.

In some embodiments, the controller 110 may identify parameters (i.e.,KPI's) associated with the various cell sites and then create one ormore cell clusters based at least in part on the KPI's. For example, thefirst cluster may comprise cell sites 102(1), 102(4) and 102(6), asdenoted by way of example in FIG. 1 by the designation C1. A secondcluster may comprise cell sites 102(2) and 102(5), as denoted by thedesignation C2. A cell site need not be part of a cluster in order to beoptimized by the central controller 110. Rather, cell sites that exhibitcommon KPI values may be grouped together for common control as acluster. In some embodiments, cell sites that exhibit KPI values thatare indicate a requirement of an adjustment are grouped together forcommon control. Thus, each cell may be controlled independently, andwhile clustering may be performed, it need not be based on geographicproximity but on common performance indicators. In this way, thewireless telecommunication network 100 can be optimized efficiently. Thedetermination of the parameters (i.e., KPI's), various adjustmentsperformed for a cell site, formation of the clusters, collection ofKPIs, and other operations of the controller 110 are explained infurther detail below.

Illustrative Computing Architecture

FIG. 2 is a block diagram of an illustrative controller 200 to optimizenetwork performance of cell sites. The controller 200 may be used toimplement the functions of the central controller 110 of FIG. 1.Accordingly, controller 200 may include various modules that perform thefunctions to optimize the performance of cell sites individually. Insome embodiments, the controller 200 also creates and defines groups ofcell sites, referred to herein as clusters, adds or assigns cell sitesto the clusters, and performs optimizations to the cell sites 102(1) to102(N) of each cluster to optimize the overall network performance. Invarious embodiments, the controller 200 may be hosted by one or moreservers in a non-distributed configuration (e.g., server farm, etc.,) ora distributed configuration (e.g., cloud service, etc.).

The controller 200 may include one or more processors 202 and memory 204that stores various modules, applications, programs, or other data. Thememory 204 may include instructions that, when executed by the one ormore processors 202, cause the processors to perform the operationsdescribed herein for the controller 200 (e.g., the central controller110). The memory 204 may include, but is not limited to, non-transitorymemory that may include hard drives, floppy diskettes, optical disks,CD-ROMs, DVDs, read-only memories (ROMs), random access memories (RAMs),EPROMs, EEPROMs, flash memory, magnetic or optical cards, solid-statememory devices, or other types of media/machine-readable medium suitablefor storing electronic instructions. In some embodiments, the memory 204may include transitory signals, such as signals that a computer systemor machine hosting or running a computer program can be configured toaccess, including signals downloaded through the Internet or othernetworks.

In the illustrated example, the memory 204 may include an operatingsystem 206 and various applications, such as an optimization manager 208that may be used to optimize the performance of individual cell sitesand/or clusters of cell sites. Execution of the optimization manager 208by the processor(s) 202 configures the controller 200 to perform variousfunctions. In one embodiment, these functions may be controlled bydifferent modules, such as a parameter module 210, data acquisitionmodule 212, optimization module 214, cluster module 216, analysis module218, reporting module 220, etc. The operating system 206 may be used toimplement these modules. The operating system 206 may be any operatingsystem capable of managing computer hardware and software resources. Themodules discussed herein may include routines, program instructions,objects, and/or data structures that perform particular tasks orimplement particular abstract data types.

The parameter module 210 may identify various parameters associated withthe cell sites, referred to herein as KPI's. The parameters may includemetrics, attributes, or other associated data for each cell site. Someof the parameters may be time-dependent, such as parameters that provideinput/output data, service data, performance data (e.g., power used,dropped calls, etc.,). Other parameters may not be time dependent, suchas location information, software specifications, hardwarespecifications, network attributes, etc. The parameter module 210 mayidentify available parameters and, in some instances, identifyparameters that impact, drive, or are associated with key result areasto enable optimization of the network performance. In variousembodiments, the parameter module 210 may receive input from a datasource, such as a server that is configured to provide baselineinformation for individual cells, clusters of cells, and/or the entirewireless telecommunication network, similar to the data server 112 ofFIG. 1. In some embodiments, the parameter module 210 may also receiveuser input, such as input from an administrator and/or engineer toassist in identification, labeling, or other tasks associated with theparameters.

The data acquisition module 212 may retrieve the parameters from varioussources. For example, the data acquisition module 212 may link tablesmaintained and updated by various servers, such as the data server 112.The acquisition module 212 may compile the parameters over apredetermined period of time. The acquisition module 212 may performbasic operations on the obtained data, such as calculate an average, amean, a maximum value, a minimum value, and/or perform othercalculations using the obtained data. The data acquisition module 212may also retrieve network attributes from various servers, such as thedata server 112, or from individual cell sites 102(1) to 102 (N), eitherdirectly or through servers such as the data server 112.

The optimization module 214 determines one or more parameters (ornetwork attributes) to optimize (i.e., adjust) for each cell siteindividually. In some scenarios, the optimization module may be used tooptimize one or more parameters of clusters of cell sites. Theoptimization module 214 may optimize each cell site and/or cluster ofcell sites in different ways. For example, the optimization module 214may increase a value or setting for a first parameter associated with afirst cell site and may decrease a value or setting for a secondparameter for a second cell site. In some embodiments, the optimizationmodule 214 may make different adjustment based on the values of theparameters or KPI's of a cell site. For example, a first cell site mayreceive a first adjustment while a second cell sites may receive asecond adjustment that is different than the first adjustment. Inanother example, a first cell site in the first cluster may receive afirst adjustment while a second range of cell sites in the first clustermay receive a second adjustment that is different than the firstadjustment.

As discussed previously, in some embodiments, adjustments to parametersare performed to clusters. In this regard, the cluster module 216 maydefine a cluster based at least in part on the parameters received fromthe data acquisition module 212. For example, the cluster module 216 mayidentify key parameters that have associated conditions. Cell sites thatinclude the key parameters that have satisfied the conditions (e.g.,exceed a threshold value, below a threshold value, etc.,) may beincluded (e.g., added, assigned, etc.,) in the cluster. Thus, thecluster is defined by cell sites that include parameters having specificranges of values. In some embodiments, the clusters are not definedbased on geographic region, but on similar KPI values.

The analysis module 218 may analyze performance of the cell sites and/orthe various components of the wireless telecommunication network 100following implementation of the optimization. In various embodiments,the analysis module 218 may initiate retrieval of data from a dataserver 112 via the data acquisition module 212. For example, theanalysis module 218 may refer to historic data of one or more cell sitesto determine a baseline performance of one or more KPI's for the one ormore cell sites. To that end, the analysis module 218 triggers the dataacquisition module to interact with the data server 112 to retrievestored historical data regarding the relevant one or more cell sites.

In one embodiment, the analysis module 218 can trigger the clustermodule 216 to cluster a group of cell sites that are deemed by theanalysis module to belong together. Similarly, the analysis module 218can trigger the cluster module 216 to undo a cluster or to remove a cellsite from a cluster if it deems that the cell site no longer belongs toa cluster, based on the analysis performed.

The reporting module 220 may report results of the performance of thecell sites and/or the various components of the wirelesstelecommunication network 100 following implementation of theoptimization. The reporting module 220 may be used to trigger asubsequent refreshing of the optimizations, clustering, or other tasksperformed by the optimization manager 208 at predetermined intervals orupon a trigger event.

In the illustrated example, the controller 200 may further includeinput/output interface(s) 222. The input/output interface(s) 222 mayinclude any type of output interface known in the art, such as a display(e.g., a liquid crystal display), speakers, a vibrating mechanism, or atactile feedback mechanism. Input/output interface(s) 222 also includeports for one or more peripheral devices, such as headphones, peripheralspeakers, or a peripheral display. Further, the input/outputinterface(s) 222 may further include a camera, a microphone, akeyboard/keypad, or a touch-sensitive display. A keyboard/keypad may bea push button numerical dialing pad (such as on a typicaltelecommunication device), a multi-key keyboard (such as a conventionalQWERTY keyboard), or one or more other types of keys or buttons, and mayalso include a joystick-like controller and/or designated navigationbuttons, or the like.

In the illustrated example, the controller 200 may further include oneor more network interface(s) 224. The one or more network interface(s)224 may include any sort of transceiver known in the art. For example,the one or more network interface(s) 224 may include a radio transceiverthat performs the function of transmitting and receiving radio frequencycommunications via an antenna. In addition, the one or more networkinterface(s) 224 may also include a wireless communication transceiverand a near field antenna for communicating over unlicensed wirelessInternet Protocol (IP) networks, such as local wireless data networksand personal area networks (e.g., Bluetooth or near field communication(NFC) networks). Further, the one or more network interface(s) 224 mayinclude wired communication components, such as an Ethernet port or aUniversal Serial Bus (USB).

Example Computing Architecture

Reference now is made to FIG. 3, which illustrates an example schematicdiagram of a computing architecture 300 that can be used to performvarious functions described herein, including automatically optimizing acell individually, and automatically clustering of cell sites foroptimization of a network. The architecture 300 may include anoptimization manager 308. For illustrative purposes, the optimizationmanager 308 includes the data acquisition module 312, the cluster module316, and the optimization module 314, although the optimization modulemay include other modules or data.

In accordance with various embodiments, the data acquisition module 212may receive data from various data sources represented herein by dataserver 312. The data sources may include historical data 306 related tohardware, services, or other related data. In some instances, thehistorical data 306 may be located in separate tables, locations, and/ormay be controlled or managed by other entities. For example, thehistorical data 306 may include customer survey information collected bya third party.

The data acquisition module 312 receives the historical data 306 fromthe data server 312 and provides the data to the cluster module 316 forassociation with respective cell sites. As discussed above, the dataacquisition module 312 may perform some calculations of the data priorto optimizing various parameters of a cell site.

In various embodiments, the cluster module 316 may receive the data fromthe data acquisition module 212 and inputs 302. The inputs 302 mayinclude data associated with the cell sites such as, and withoutlimitation, an area of the radio network controller, baseline dates(time period), metrics to optimize, thresholds for the metrics, and/orother associated data, represented collectively as new data 304 in theexample of FIG. 3.

Upon receiving the relevant data from the data server 312 and/or theinputs 302, the optimization manager 308 may provide the gatheredhistorical data 306 and the new data 304 to the optimization module 314to optimize the performance of a cell site. In one embodiment, upon thedata acquisition module 312 determining that other cell sites are havingsimilar KPI's that have exceeded predetermined thresholds, these cellsmay be grouped together in a cluster by the cluster module 316.Accordingly, in various scenarios, the optimization performed by theoptimization module 314 may be with respect with an individual cell site(e.g., 302(4)) or a cluster (e.g., 302(10, 302(4) and 302(6)).

For example, the optimization module 314 may receive data (i) directlyfrom the data acquisition module 312, or (ii) from the cluster module316 with information regarding the cell sites that belong to thecluster. The optimization module 314 may then perform the optimizationto create optimization results 320, which may be deployed to a cell siteindividually or to a cluster. The optimization results 320 may includeparameter changes, implementation instructions, scripts to perform thechanges, and/or other data to deploy the optimization for each cell siteindividually or in aggregate (i.e., group) for a cluster.

It should be noted that, in one embodiment, when a cluster is created,it need not be permanent. Rather, the optimization manager 308 maycreate a different cluster at predetermined intervals or upon a triggerevent. For example, a new cluster may be automatically created by theoptimization manager 308 upon the data acquisition module 312 receivingdata from the data server 312 and/or the inputs 302 and determining thata group of cell sites are exhibiting similar KPI's that warrant aperformance correction. By automating the operations described herein,the optimization manager 308 dynamically manages the wirelesstelecommunication network 100 by optimizing the performance of each cellsite individually or in specific clusters of cell sites.

Example Processes

With the foregoing overview of an example network 100 that facilitatesthe optimization of the performance of a wireless telecommunicationnetwork by adjusting one or more parameters of a cell site or a clusterof cell sites of FIG. 1, it may be helpful to provide some exampleprocesses. To that end, FIGS. 4 to 5 illustrate flow diagrams of exampleprocesses to optimize the performance of a wireless telecommunicationnetwork. The processes are illustrated as a collection of blocks in alogical flow graph, which represent a sequence of operations that can beimplemented in hardware, software, or a combination thereof. In thecontext of software, the blocks represent computer-executableinstructions that, when executed by one or more processors, cause theone or more processors to perform the recited operations. Generally,computer-executable instructions include routines, programs, objects,components, data structures, and the like that perform particularfunctions or implement particular abstract data types. The order inwhich the operations are described is not intended to be construed as alimitation, and any number of the described blocks can be combined inany order and/or in parallel to implement the processes. For discussionpurposes, the process 400 and 500 are described with reference to thearchitecture 100 of FIG. 1, the controller 200 of FIG. 2, and thecomputing architecture of FIG. 3.

The process 400 may be performed by the optimization manager 208 of acentral controller 110 of a wireless telecommunication network 100. Atblock 402, the data acquisition module 312 of the controller 200 mayreceive historical data 306 and new data 304 from various sources, suchas inputs 302 and the data server 312 of FIG. 3. The historical data 306and/or the new data 304 can be used to create a baseline performance ofeach cell site. In one embodiment, the baseline performance may be basedon KPI's of each individual cell site that have been stored in the dataserver 312 to indicate an average expected operation of the respectivecell site for each KPI. In other embodiments, the KPI's may be based onnew data 304, which is used to identify average KPI's for all cell sitesor cell sites that were grouped together by similar capability toidentify a present average of all cell sites of the wirelesstelecommunication network 100 or similarly situated cell sites. In otherembodiments, the KPI's are based on predetermined values that may havebeen programmed by an administrator of the wireless telecommunicationnetwork 100.

At block 404, the optimization manager 308 identifies parameters tooptimize. For example, the KPI's, which may be based on the new data304, are compared to the baseline(s) to identify outliers therefrom. Ifone or more KPI's have exceeded predetermined thresholds based on therelated baseline, then it is indicative that one or more parametersshould be adjusted.

At optional block 406, the optimization manager 308 (i.e., clustermodule 316 thereof) determines whether other cell sites have KPI's thathave exceeded similar baseline thresholds. If so (i.e., “YES” atdecision block 406), at block 408, these cell sites are grouped togetherinto a cluster. However, if other cell sites are not identified havingsubstantially similar KPI issues, (i.e., “NO” at decision block 406),the process continues with block 410, where the optimization manager 308focuses on an individual cell site to optimize.

Accordingly, clusters may be identified as groupings of cell sites thathave the same or similar performance patterns based on the parameters(received data), rather than on arbitrary information, such asgeographical designation (e.g., city, rural, etc.,). In someembodiments, the number of cell sites per cluster may be limited to apredetermined number to assure that each cell site is optimized, insteadof suffering from the consequences of an adjustment of parameters thatis not optimal for each individual cell site, but rather accommodates an“average” cell site benefit.

At block 411, the optimization manager 308 identifies the optimizationobjective of the present performance optimization. In one embodiment,there may be two modes of optimization, namely: (i) LTE network coverageand performance and (ii) LTE network layer management optimization.Based on the optimization objective, a different optimization flow maybe followed. In various embodiments, the optimization objective may bedifferent for different regions, time periods, and/or events. Forexample, LTE network layer management (i.e., path 1) may be applied toregions that have a dense population, whereas LTE network coverage andperformance (i.e., path 2) may be applied to regions that have a lessdense population. In some embodiments, one path may be applied after theother.

Upon identifying that an LTE network layer management objective (i.e.,path 1) should be followed in block 411, at block 412, the optimizationmodule 314 may apply one or more correction modules 420 to 434 tooptimize (e.g., adjust) various aspects of each cell site individually(or by way of cluster). The modules 420 to 434 that are applied dependon the one or more KPI's that have exceeded predetermined thresholdvalues based on determined baselines, as discussed previously. In someembodiments, the optimizations may include changes to one or moreparameters of a cell site. For example, at block 420, a load balance andthroughput module may be applied. In this regard, at block 422, wirelessdata traffic is moved between LTE layers to balance traffic and toimprove throughput. More specifically, layers with more traffic and/orless throughput (i.e., data rate) have their traffic placed on otherlayers with less traffic and/or higher throughput.

At block 430, a leakage module may be applied to keep traffic longer onthe LTE network to reduce LTE Leakage (i.e., block 432). For example, atblock 430, cell sites with very good retain-ability (i.e., drop callrate) can be optimized to extend its usable LTE coverage, by performinga trade-off between retain-ability and LTE Leakage.

At block 434, the layer management module may be applied. To that end,at block 436, mobility on a specific service/layer is triggered to movetraffic from one layer to another, thereby providing better layerperformance and layer management over the wireless communication network100.

In various situations, one or more correction modules may be used tocreate the optimization results message (i.e., block 480). These blockscan then be distributed to an individual cell site or the cluster ofcell sites, accordingly.

Returning to block 411, upon identifying that an LTE network coverageand performance objective (i.e., path 2) should be followed, then atblock 413, the optimization module 314 may apply one or more correctionmodules 440 to 460 to optimize (e.g., adjust) various aspects of eachcell site individually (or by way of cluster). The modules 440 to 460that may be applied depend on the one or more KPI's, as discussed above.

At block 440, the uplink (UL) and/or downlink (DL) coverage module maybe applied. For example, to improve the UL coverage, at block 442, theUL power is increased to improve UL coverage and to reduce the number ofdropped calls. Similarly, the DL coverage can be improved by increasingthe DL power.

At block 450, the interference module may be applied, where at least oneof (i) the reference symbol power is reduced, and (ii) the controlchannel elements (CCE) position in the LTE Radio Frame is modified torandomize and reduce the interference and improve transmission quality(i.e., block 452).

At block 460, the mobility module may be applied, where handovers (HOs)are optimized. For example, at block 462, the offsets on the HOthresholds are adjusted to minimize drops in calls. Put differently, thenumber of handovers are reduced, which may be prone to dropped calls(e.g., failed handovers), by increasing the threshold that would triggera handoff. Alternatively, the thresholds may be reduced to increase thenumber of handoffs are increased to prevent too late handovers.

One or more correction modules may be used to create the optimizationresults message (i.e., block 480). These blocks can then be distributedto an individual cell site or the cluster of cell sites, accordingly. Inone embodiment the optimization results message includes theinstructions of the one or more correction modules 412 of the first pathand the one or more correction modules 413 of the second path. In otherembodiments, each path creates a separate optimization results message.By virtue of adjusting or setting parameters for each cell site that isdeemed to have KPI's that exceed predetermined thresholds, the wirelesstelecommunication network 100 is optimized for performance.

FIG. 5 is a flow diagram of an illustrative process 500 that iterativelyadjusts parameters of an individual cell site or cluster of cell sites.The process 500 may be performed by the optimization manager 308 andvarious modules associated therewith.

At block 502, the data acquisition module 312 of the controller 200 mayreceive historical data 306 and new data 304 from various sources, suchthe data server 112 and inputs 302, respectively. The historical data306 and/or the new data 304 can be used to create a baseline performanceof each cell site (i.e., block 504). The historical data 306 and the newdata 304 are collectively referred to herein as network data. In oneembodiment, the baseline performance may be based on KPI's of eachindividual cell site that has been stored in the data server 312. Thisdata indicates an average operation of the respective cell site for eachKPI. In other embodiments, the KPI's may be based on new data 304, whichis used to identify average KPI's for all cell sites (or cell sites thatare grouped together by similar capability). In other embodiments, theKPI's are based on predetermined values that may have been programmed byan administrator of the wireless telecommunication network 100.

At block 506, the optimization manager 308 identifies the optimizationobjective of the present performance optimization. In this regard, theremay be two modes of optimization, namely: (i) LTE network coverage andperformance and (ii) LTE network layer management. Based on theoptimization objective identified in block 506, a different optimizationflow may be followed. As discussed previously, in various embodiments,the optimization objective may be different for different regions, timeperiods, and/or events. Depending on the optimization objective, path 1may be run without path 2 or path 2 may be run without path 1. In someembodiments, both paths 1 and 2 may be run one after another (in anyorder) or concurrently.

Upon identifying that the optimization objective is LTE Network LayerManagement (i.e., identifying path 1 in block 506), the processcontinues with block 508, where the optimization manager 308 identifiesparameters to optimize. For example, the KPI's, which may be based onthe new data 304, are compared to the baseline(s) to identify outlierstherefrom. If one or more KPI's have exceeded predetermined thresholdsbased on the related baseline, then such deviation is indicative thatone or more parameters should be adjusted, and the cell site is deemedto be non-compliant.

In one embodiment, upon the optimization manager 308 identifyingparameters to optimize, the cluster module 316 determines whether othercell sites are having similar KPI's that have exceeded predeterminedthresholds. If so, these cell sites may be grouped together in a clusterby the cluster module 316, and the following operations of the firstpath of process 500 (i.e., 510 to 516) are performed on a cluster ofcell sites.

At block 510, load balancing is performed by comparing a normalized userequipment (UE) downlink (DL) throughput at a first cellular frequencyband to a second cellular frequency band. For example, there may bemultiple LTE layers (e.g., LTE 2100 MHz, LTE 700 MHz, etc.,) that are inservice for the wireless communication network 100. Due to the differentRF conditions between the different LTE layers (e.g., due to differentfrequency and/or site design), the data rate (i.e., the data throughputexperienced by a user) varies between these layers. By virtue of loadbalancing, a user of the wireless telecommunication network 100 isprovided a uniform and optimized throughput.

In various embodiments, the optimization manager 308 determines whetheran individual cell site, a cluster of cell sites, or the wirelesscommunication network 100 in aggregate, has a first cellular frequency(e.g., LTE 2100) data rate “X” that is lower than that of anothercellular frequency (e.g., LTE 700) by a predetermined number “Y.” If so,the subscribed customers of the corresponding cell site (or cluster) isswitched to the better performing cellular frequency (e.g., customersare switched from the LTE 2100 to L700 layer).

For example, the Load Balance and Throughput correction module 420 ofFIG. 4 can be used to move user equipment (UE) that are using thewireless telecommunication network 100 from the LTE 2100 layer to theLTE 700 layer. Further, the “Load Balancing Threshold” (lbThreshold)parameter, which defines the delta load between two layers upon whichthe actions of the Load Balancing and Throughput correction module 420actions are triggered, is adjusted to move the traffic from the LTE 2100layer to the LTE 700 layer. For example, the source layer (e.g., LTE2100 layer in this example) coverage threshold (a5Threshold1RSRP) isadjusted to a higher value, so more connected users on LTE 2100 layerwill be eligible to be moved to the LTE 700 layer via this loadbalancing functionality. In one embodiment, for the UE that are moved tothe LTE 700 layer, to retain them on that layer longer, the “LoadBalancing Activation Threshold” (lbActivationThreshold) is adjusted to ahigher value. Such adjustment facilitates the movement of the trafficfrom a “high loaded layer” to a “low loaded layer,” thereby providingload balancing to the cell site and improving overall performance of thewireless telecommunication network 100.

Similarly, the Load Balance and Throughput correction module 420 of FIG.4 can be used to move UE from the LTE 700 to the LTE 2100 layer upon theoptimization manager 308 determining that the LTE 700 layer has a datarate that is lower than that of the second cellular frequency (e.g., LTE2100 in this example) by a predetermined number “X.” If so, thesubscribed customers of the corresponding cell site (or cluster) isswitched to the better performing cellular frequency. Rows 600A and 600Bof the table of FIG. 6A provide a summary of relevant KPI's and examplesolutions for load balancing.

At block 512, the cellular coverage is optimized. It is noted that theLTE's usable coverage footprint is not simply limited by the physicalimplementation of the cell site and the radio propagation in the airinterface. Rather, the coverage may also be affected by various networkparameters. In one embodiment, prevailing network parameterconfigurations limit the coverage foot print, such that the quality ofservice (QOS), which may manifest itself, for example, as retain-abilityof a channel with the wireless telecommunication network 100, isimproved. For example, QOS (e.g., retain-ability or drop call rate) of acell site is better than necessary, (e.g., higher than a predeterminedthreshold reference, which may be based on an average of a plurality ofcell sites). In such scenarios, by virtue of performing a trade-offbetween coverage and retain-ability, the effective usable LTE coverageis improved, with negligible degradation to retain-ability or drop callrate. Accordingly, more UE can stay on LTE coverage and for a longerduration, thereby reducing LTE Leakage.

The criteria used for performing the cellular coverage optimization maybe based on determining whether a cell site (i) has a drop call ratethat is below a predetermined threshold percentage “X,” (ii) the cellsite has at least a second predetermined number “Y” VoLTE voice calls ina predetermined time period, (iii) the data rate (i.e., user experiencedthroughput) on the cell site is higher than a third predetermined value“Z” Mbps, and (iv) the percentage of calls that are leaking (i.e.,moving away from LTE) towards a Universal Mobile TelecommunicationsSystem (UMTS) is higher than a fourth number “A” %. For example, thepercentage of calls that are subject to leakage may be calculated usinga combination of “PS Handover” and “Session Continuity” to UMTS fromLTE. As used herein, the term “drop call rate” may be with respect to afraction of the calls that, due to technical reasons, were cut offbefore the speaking parties had finished their conversation and beforeone of them had hung up. In various embodiments, this fraction can bemeasured as a percentage of all calls in a predetermined time period.

Upon determining that the criteria are met, the session continuity andpacket switched (PS) handover trigger points from LTE to UMTS may bedelayed. Further, the trigger at which the LTE calls are releasedthrough a “Session Continuity” parameter (i.e., a2CriticalThresholdRsrp)is reduced by a predetermined value “X” dB. The PS Handover triggervalue from LTE to UMTS parameter (i.e., b2Threshold1Rsrp), may bereduced by a predetermined value “Y” dB. The time it takes to measureand trigger the PS hander (i.e., timeToTriggerB2), by a predeterminedduration “X” milliseconds may be delayed. By virtue of tweaking theseparameters by the leakage module 430 of FIG. 4, the session continuityand PS handover from LTE to UMTS is reduced, thereby reducing the LTELeakage, with little to no impact on retain-ability or a drop call rate.Row 600C of the table of FIG. 6A provides a summary of relevant KPI'sand example solutions for optimization of cellular coverage.

At block 514, a layer management operation is performed by the layermanagement correction module 434 of FIG. 4. For example, calls from onecommunication layer are moved to another communication layer based ondetermined drop call rates for each communication layer. Consider, forexample, that when adding a new layer in the existing wirelesstelecommunication network 100, based on the deployment schedules, cellsites with the new layer (e.g., LTE 700) may be available in some areas,which may be not contiguous. Such scattered deployment may lead to somecells to have an unintended coverage foot print. Thisunintended—extended coverage foot print of such cell sites often causesmultiple performance issues to users of the wireless telecommunicationnetwork 100 via their UE. In one embodiment, the optimization manager308 is configured to identify such cell sites and provide the properlayer management for an improved customer experience.

The criteria for performing a layer management by the optimizationmanager 308 may be based on comparing the drop call rates for bothcommunication layers. For example, the optimization manager 308determines whether: (i) the subject cell site a first layer (e.g., LTE700) has a VoLTE drop call rate greater than a predetermined percentagevalue; (ii) the cell site drop call rate of the second layer (e.g., LTE2100) has a VoLTE drop call rate less than a second predeterminedpercentage rate; (iii) the first layer (e.g., LTE 700) has at least athird predetermined number of VoLTE voice calls during a predeterminedtime period; (iv) a “bad coverage” indicator in the first layer (e.g.,LTE 700) is greater than a fourth predetermined percentage value; (v) a“bad coverage” indicator in the second layer (e.g., LTE 2100) is lessthan a fifth predetermined percentage value; and (vi) the averageReceived Signal Level (RSRP) of the first layer (e.g., LTE 700) is asixth predetermined dB value weaker than that of the second layer (e.g.,LTE 2100).

In one embodiment, the “bad coverage indicator” is calculated using thepercentage value of calls that are triggering “bad coverage”measurements out of a total number of calls during a predeterminedperiod on the subject cell site. Alternatively, or in addition, the “badcoverage indicator” for a cell site can also be calculated using a “celltrace” based coverage measurement reports, processed through ageo-location capable tool, such as, without limitation, “True Call.”

Upon determining that the criteria are met, the optimization manager 308moves the call sessions from the first layer (e.g., LTE 700) to thesecond layer (e.g., LTE 2100) through an inter frequency HO. Further,the usable foot-print of unintended extended coverage is limited by idlemode parameter configuration. The “bad coverage” measurement triggerparameter (i.e., a1a2SearchThresholdRsrp) may be increased by apredetermined dB value. The “Critical Session Continuity” triggerparameter (i.e., a2CriticalThresholdRsrp) may be increased by apredetermined dB value. Still further, the idle mode—usable coveragefoot print parameter (i.e., qRxLevMin) is increased by a predetermineddB value.

Similarly, the layer management correction module 434 may be used tomove calls from the second layer (e.g., LTE 2100) to the first layer(e.g., LTE 700). Rows 600E and 600F of the table of FIG. 6B provides asummary of relevant KPI's and example solutions for optimization of thelayer management for poor coverage of the first and second layers,respectively.

At block 516, the performance of the cell that has been optimized ismonitored. For example, the data acquisition module 312 of thecontroller 200 may receive new data 304 from various sources, such asfrom inputs 302 and the data server 112, to obtain the latest KPI'stherefrom related to the subject cell site. The new data 304 can be usedto compare the new performance of the cell site to the baselineperformance, thereby determining (i.e., block 520) whether theoptimization is successfully realized (e.g., determining whether theadjusted performance of the cell site is within a baseline performancerange of the wireless telecommunication network 100 that was calculatedpreviously at block 504).

Upon determining that the desired optimization is achieved (i.e., “YES”at decision block 520), the optimization manager 308 concludes that thesubject cell site is within predetermined one or more ranges of thebaseline previously calculated in block 504. The process then loops backto block 502 to receive network data, after a waiting period (i.e.,block 522), thereby restarting the process. By way of non-limitingexample, the wait period may be a periodic interval such as an hour, aday, a week, quarterly, etc. Accordingly, the wait period may be anyappropriate wait period to maintain the wireless telecommunicationnetwork 100 in an efficient way. In some embodiments, there may be atrigger to override the wait period, such that the process beginsimmediately. In various embodiments, a trigger event may be a natural,social, or architecture event (e.g., hurricane, concert, introduction ofnew cell sites, etc.,).

Returning to block 520, upon determining that the desired optimizationis not achieved (i.e., “NO” at decision block 520), the processcontinues with block 508, to identify parameters to optimize, asdiscussed previously. The iterative process continues until the desiredoptimization is achieved (i.e., the monitored performance at block 546indicates that the KPI's of the subject cell site are within apredetermined ranges of the baseline calculated previously in block504).

Returning to block 506, upon identifying that an LTE network coverageand performance objective (i.e., path 2) should be followed, then theprocess continues with block 536, where the optimization manager 308identifies parameters to optimize. For example, the KPI's related to theLTE network coverage and performance, which may be based on the new data304, are compared to the baseline(s) to identify outliers therefrom. Ifone or more KPI's have exceeded predetermined thresholds based on therelated baseline, then such deviation is indicative that one or moreparameters should be adjusted, and the cell site is deemed to benon-compliant.

At block 538, optimization of uplink (from UE to cell site) transmissionpower is performed. More particularly, for UEs whose transmitted powerreached the allowed maximum value (UEs with higher power restrictionratio), the UL transmission power is reduced. Put differently, thecriteria for performing an optimization of transmission power may bebased on determining whether the cell site: (i) has a predeterminedpercentage of time where the UE's transmitted power reaches a maximumvalue is greater than a predetermined reference threshold percentage(i.e., a power restriction ratio); (ii) the VoLTE drop call rate of thecell site is greater than a predetermined percentage; and (iii) thereare at least a predetermined number of VoLTE voice calls hosted by thecell site in a predetermined time period.

In this regard, it is noted that an LTE's usable coverage can becharacterized by a downlink (DL) (i.e., from a cell site to a UE)coverage parameter and an uplink (UL) (i.e., from a UE to a cell site)coverage parameter. Both links are salient for any calls for sustainablecall quality. For example, there may be multiple cells where, at thecell edges, there could be a good or acceptable downlink coverage, butvery weak to no uplink coverage. At the weaker uplink coverage, the UE'spower may not be sufficient to communicate to the baseline, which leadsto poor QOS. By the optimization manager 308 using the UL/DL coveragecorrection module 440 of FIG. 4, a cell site that has been identified tohave a power restriction issue is corrected, thereby extending the ULcoverage and improving the QOS (e.g., throughput, retain-ability, etc.,)of the UE using the affected cell site.

Upon determining that the criteria are met, the “Required Power SpectralDensity (PSD)/Received Power at: the cell site on the uplink parameters(i.e., pZeroNominalPusch) are increased by a predetermined dB value.Further an ‘Alpha’ that governs the slope of curve between Received PSDand Uplink Path-loss, is reduced by a predetermined value. By virtue ofthese adjustments performed by the UL/DL coverage correction module 440of FIG. 4, the PSD at lower uplink path-loss (i.e., close to the cells)is increased, thereby providing better QOS (e.g., throughput,retain-ability, etc.,) for UEs closer to the cell station. At the sametime, for the UE at the cell edges, the “Required PSD” reduces, whichassists UEs to transmit at a lower power, thereby reducing the UE's“Power Restriction,” reducing UL Interference, and improving UL coverageand QOS for the respective UE. Row 600D of the table of FIG. 6A providesa summary of relevant KPI's and example solutions for optimization ofthe power restriction.

At block 540, optimization of downlink (from cell site to UE)transmission power is performed by adjusting a gain of a cell specificreference signal (CRS) of the subject cell site by the optimizationmanager 308. For example, it is understood that with a growing cell siteintensity (i.e., higher number of cell sites within a geographical area)in the wireless telecommunication network 100, inter site interferencemay become an increasing concern in traditional systems. There areseveral ways to reduce inter-site interference, including reducingtransmission power. However, reducing the transmission power in all cellsites, has an impact on the coverage foot-print, which may detrimentallyaffect the quality of service to users of the wireless telecommunicationnetwork 100. In this regard, the optimization manager 308 identifieswhether each individual cell site has a sufficient coverage foot-printto warrant a reduction of the downlink transmission power. Putdifferently, the transmission power is adjusted automatically by theoptimization manager 308 for each cell site individually.

The criteria for determining whether to reduce the downlink (DL)transmission power may include determining whether: (i) the sessioncontinuity to older communication networks, such as, without limitation,Wideband Code Division Multiple Access (WCDMA) and Global System forMobile Communications (GSM) are less than a predetermined thresholdpercentage value; and (ii) a predetermined percentage of HO attempts arehappening to ‘neighboring cells (excluding geographically co-locatedcells) at a distance less than the average neighbor distance of the cellsite.’ This is to make sure that there is a sufficient amount ofcoverage overlap between a cell site and its neighbors, such thattransmission power reduction will not cause a coverage loss. Additionalcriteria may include determining whether (iii) an average busy hourchannel quality index (CQI) for a subject cell site plus a predeterminedtop number of closest neighbors (e.g., 5) based on HO attempts is belowa predetermined threshold value. In this way, the optimization manager308 verifies that there is an “inter site interference” issue in thecoverage foot-print of the subject cell site.

Upon determining that the criteria are met, the downlink (DL)transmission power is reduced through a parameter (i.e., crsGain) by apredetermined dB value. If the crsGain parameter is changed to 0 dB, theDL Transmission Power on the physical downlink shared channel (PDSCH)Type B channel parameter (i.e., pdschTypeBGain) is increased. Additionalpower on the PDSCH Type B, may enhance the data rate (e.g., userthroughput). By lowering crsGain parameter on the subject cell site,which met the above discussed criteria, the optimization manager 308prevents loss of wireless telecommunication coverage while minimizingthe inter site interference. Row 600G of the table of FIG. 6B provides asummary of relevant KPI's and example parameter adjustments foroptimization of the CRS.

At block 542, the handover (HO) between a first cell site and a secondcell site is adjusted for various issues, including without limitationfor, (i) physical downlink control channel (PDCCH) robustness, (ii) toolate HO, (iii) too early HO, and (iv) mobility optimization (i.e.,prevention of handover to a wrong cell site).

Robustness of handover is based on determining whether a CFI1utilization is above a predetermined threshold and a HO Executionsuccess rate is below a predetermined threshold. Typically, in a highmobility region (e.g., where UE traverses one or more cellular zones anda handover is likely), the UE may have access to multiple LTE cells. Ifthe “control signaling message” parameter, through a PDCCH channel, istransmitted on the first Orthogonal Frequency-Division Multiple Access(OFDMA) symbol in the LTE frame (CFI=1), there is a possibility ofcollision of that communication with other neighboring cells. Thiscollision is due to most cells transmitting similar messages on CFI=1 tothe subscribed users on their UE. This collision could lead to ahandover failure, which impacts a customer's QOS. To that end, theoptimization manager provides a way to identify cell sites that havesuch handover failures and provides a solution therefor.

The criteria for determining whether to adjust the PDCCH handoverparameters may include determining whether: (i) a subject cell with theutilization of the first OFDMA symbol (CFI=1) is greater than apredetermined percentage value; and (ii) the handover execution successrate is below a predetermined percentage.

Upon determining that the criteria are met, the optimization manager 308prohibits the use of the first OFDMA symbol (CFI=1) for users in thehandover region, by adjusting a 3GPP parameter (i.e.,adaptiveCfiHoProhibit to 1). Further, instead of CFI=1, the subject cellsite could be adjusted to use CFI 2 or 3. This prohibition facilitatesthe reduction of the transmission on CFI=1 in the handover region (wheremultiple cells overlap), thereby minimizing and randomizing the intersite interference on the PDCCH. Accordingly, the handover success rateis improved. In some scenarios, the retain-ability for the cell site isimproved as well. Row 6001 of the table of FIG. 6B provides a summary ofrelevant KPI's and example parameter adjustments for optimization of thePDCCH handover.

In some embodiments, the PDCCH power is boosted for cells requestingmore than a threshold number of control channel elements (CCE). Thecriteria for determining whether to adjust the PDCCH power may includedetermining whether: (i) a predetermined percentage of time a cell siteprovides a predetermined number (e.g., 8) CCE Aggregation (%TxAggressive) is above a first percentage value; and (ii) the PDCCHcontrol channel usage is below a second percentage value. In oneembodiment, the criteria to revert back from an active power boost is:(i) the PDCCH usage is above a third threshold percentage value; and(ii) the parameter TxAggressive is below a fourth threshold value. Thefirst, second, third, and fourth threshold values may be default valuesor values that are tailored for the specific cell site by a systemadministrator.

Upon determining that the criteria for PDCCH power boosting are met, theboosting power on the DL control channel is adjusted by settingparameter pdcchpowerboostmax=P (where P is a non-zero value), for thesubject cell site. Increased PDCCH power improves PDCCH coverage,especially for cell edge users. Increased PDCCH power may help withhigher retainability (drop call rate) and higher throughput (data rate).Row 600J of the table of FIG. 6B provides a summary of relevant KPI'sand example parameter adjustments for optimization of the PDCCH power.

The handover between a first cell site and a second cell site can alsobe adjusted for the timing of the handover (e.g., a too late HO or a tooearly HO). In typical systems, the timing of the handover from a sourcecell site to a neighbor target cell site may affect the success of theactual handover, which is reflected in the number of dropped calls. Inthis regard, the optimization module 308 is configured to determinewhether a cell site has a HO timing issue and adjust various parametersin order to increase the probability of a successful transition from onecell site (i.e., source) to another (i.e., target).

The criteria for determining whether to adjust the handover parameters,various Ericsson “performance counters” may be used to identify relevantKPI's. For example, to identify a late handover, the optimizationmanager 308 determines whether: (i) the performance counter parameterPMHOTOOLATEHOINTRAF (i.e., operative to indicate a number of too latehandovers) is above a predetermined threshold X (e.g., the number of toolate handovers greater than X); (ii) the percentage value of theperformance counter parameter PMHOTOOLATEHOINTRAF is above a secondpredetermined threshold Y (e.g., percentage of too late HOs to totalhandovers greater than Y %); and (iii) the performance counter parameterindicating a number of drop calls PMERABRELABNORMALENBACTHO is above athird predetermined threshold Z (e.g., number of call drops due tohandovers greater than Z). For example, the threshold values for X, Yand Z may be predefined by a system administrator of the wirelesstelecommunication network 100 and may vary based on the region and/orthe type of cell site.

Upon determining that the above criteria are met, thereby identifying alate handover concern for a subject cell site, the parameterscellindividualOffsetEutran and QoffsetEutran are changed. These twoparameters affect the offset on a signal level to trigger a handover andreselection to a better cell. In one embodiment, the values of thecellindividualOffsetEutran and QoffsetEutran are based on therelationships provided in Table 1 below:

TABLE 1 Condition New Setting n < % of too late HOs to totalcellindividualOffsetEutran = a; handovers < m qoffsetEutran=−a m < % oftoo late HOs to total cellindividualOffsetEutran = b; handovers < oqoffsetEutran=−b % of too late HOs to total cellindividualOffsetEutran =c; handovers > o qoffsetEutran=−c

Table 1 above demonstrates that if the parameter indicative of the % oftoo late HOs to total handovers (i.e., PMHOTOOLATEHOINTRAF) is in afirst range (i.e., n to m), then parameter cellindividualOffsetEutran isset to a first predetermined value a, and the parameter qoffsetEutran isset to the opposite polarity of the same value (i.e., −a), and so on.

Similar concerns may arise when the HO from a first cell site to asecond neighboring cell site is too early. The criteria to identify ahandover that is too early, the optimization manager 308 determineswhether: (i) the parameter (e.g., a performance counter) indicative of atoo early handover PMHOTOOEARLYHOINTRAF is above a predeterminedthreshold X (e.g., the number of too early handovers greater than X);(ii) the percentage value of the parameter PMHOTOOEARLYHOINTRAF is abovea second predetermined threshold Y (e.g., percentage of too early HOs tototal handovers greater than Y %); and (iii) the parameter indicating anumber of drop calls PMERABRELABNORMALENBACTHO is above a thirdpredetermined threshold Z (e.g., number of call drops due to handoversgreater than Z). For example, the threshold values for X, Y and Z may bepredefined by a system administrator of the wireless telecommunicationnetwork 100 and may vary based on the region and/or the type of cellsite.

Upon determining that the above criteria are met, thereby identifying anearly handover concern for a subject cell site, the parameterscellindividualOffsetEutran and QoffsetEutran, which are operative tocontrol an offset on a signal level to trigger a handover andreselection to a better cell, are changed. In one embodiment, the valuesof the cellindividualOffsetEutran and QoffsetEutran are based on therelationships provided by Table 2 below:

TABLE 2 Condition New Setting n < % of too early HOs to totalcellindividualOffsetEutran =− a; handovers < m qoffsetEutran=a m < % oftoo early HOs to total cellindividualOffsetEutran = −b; handovers < oqoffsetEutran=b % of too early HOs to total cellindividualOffsetEutran =−c; handovers > o qoffsetEutran=c

Accordingly, the timing of the HO can be adjusted by the optimizationmanager 308 for both a too late and a too early HO scenario by adjustingthe relevant parameters. Rows 600K and 600L of the table of FIG. 6Cprovide a summary of relevant KPI's and example parameter adjustmentsfor optimization of the HO parameters for a too late and a too early HO,accordingly.

As mentioned previously, in typical communication networks, when a UE ismoved from one zone to another, an ongoing communication of the UE maybe handed over to an incorrect target cell, resulting in a dropped call.In this regard, the optimization manager 308 is configured to optimizethe handover process to avoid a misguided HO.

In one embodiment, the determination whether a source to target cellsite pair exhibits a HO problem is based on monitoring specific countersof the wireless telecommunication network 100 and by determining whetherthe value of the counters exceed predetermined thresholds. Moreparticularly, the criteria may be based on whether: (i) the distancefrom the source cell to target cell is above a predetermined thresholdL; (ii) the parameter PMHOWRONGCELLINTRAF is above a secondpredetermined threshold X (e.g., the number of handovers to wrong cellgreater than X); and (iii) the percentage value of the parameterPMHOWRONGCELLINTRAF is above a predetermined third threshold value Y(e.g., the percentage of handovers to a wrong cell to the totalhandovers is greater than Y % for the pair source target cell). As usedherein, the example threshold values L, X and Y may be defined by asystem administrator of the wireless telecommunication network 100 andmay vary based on the region and/or the type of cell site.

Upon determining that the criteria are met, the parameters isHoAllowedand isRemoveAllowed are adjusted to indicate that the source targetneighbor relation is incorrect and therefore such a relation is put on a“blacklist”. Accordingly, handovers to a wrong cell site aresubstantially reduced or even prevented. Row 600M of the table of FIG.6C provides a summary of relevant KPI's and example parameteradjustments for optimization of the HO parameters to prevent a wrong HO.

In one embodiment, in addition to preventing a HO to a wrong cell, theoptimization manager 308 is configured to identify cells (referred toherein as a “third cell” that receives “call re-establishments” frommultiple source cells, after failing handover attempts towards a wrongtarget cell. Call Re-establishments are referred to herein as calls,continuing to a cell, without user experiencing interruption, but notthrough a network guided handover process.

The criteria for determining call re-establishments on a source to“third cell” relation, after HO to a wrong cell, includes monitoringspecific one or more counters. For example, to identify a scenario wherereestablishing a HO is warranted, the optimization manager 308determines whether: (i) the distance from the source cell site to the“third cell” site is above a predetermined threshold distance (e.g., 4miles); and (ii) a number of HOs to a wrong cell reestablishments isabove a predetermined threshold (e.g., 20), from multiple (e.g., 5)source cells towards this “third cell” The threshold distance and thepredetermined threshold number of HOs to a wrong cell may be adjusted bya system administrator of the wireless telecommunication network 100.

In various embodiments, upon determining that the criteria are met for asource to “third cell” target cell site pair, and upon determining thatthe target cell (third cell) site is an over-shooter (e.g., has a toowide communication range), then an antenna of the target cell (thirdcell) site is tilted down by a predetermined value to reduce thecoverage of the target cell (third cell) site. By virtue of adjustingthe tilt of such sites, unnecessary overshooting of coverage is reducedand proper network guided handovers happen to the right cells, whichimproves the handover success rate and retain-ability.

At block 544, the cell site range is adjusted. Consider, for example,that every cell site in an LTE network may have a defined maximum cellrange related to a maximum distance from the cell site to a UE that canaccess the cell site. There typically is a default distance value.However, in some scenarios (e.g., rural environments, where the UE maybe more than the default distance value from a cell site and/or due to alimitation in the current setting of a maximum cell range) the UE maynot be able to access the services of the wireless telecommunicationnetwork 100. In this regard, by adjusting the cell range by theoptimization manager 308, the cell site range can be expanded.

The criteria for determining whether to adjust the cell rangeparameters, several KPIs may be used. For example, the criteria mayinclude determining at least one of: (i) whether handover executionfailures are above a predetermined threshold N; (ii) whether a randomaccess channel (RACH) decoding rate is below a threshold percentage rateM %; and (iii) whether a RACH Failure rate due to the cell rangerestriction is above a threshold percentage rate K %.

Upon determining that the criteria are met, in one embodiment, theoptimization manager 308 may increase the cellRange parameter value,thereby allowing the cell site to receive and decode RACH requests fromUE that is farther than typical. The cellRange parameter is operative tocontrol transmission range of the subject cell site range. This means,by increasing the cellRange parameter, the usable coverage of the cellis now extended. In some embodiments, before the cellRange parameter isadjusted, it is first determined whether RF shaping is required, whetherthe subject cell is overshooting, and/or whether the subject cell iscovering unintended areas. RF shaping may be a combination of manyphysical configuration changes: antenna swaps, RC changes, tilts, power,azimuths, site replacements, site takedowns, etc. The wirelesstelecommunication network 100 generally benefits from iterativefootprint optimization. In some embodiments, the cellRange parameter isadjusted without initially sending instructions to adjust the tilt ofone or more antennae of the cell site (e.g., to prevent other UE in thatarea to be disadvantaged by such adjustment).

It should be noted that in some scenarios, an LTE network may havedifferent cells sites (or layers of the same cell site) performingdifferently or cell sites in neighboring regions performing differently.For example, a VoLTE voice drop call rate (VoLTE DCR) may be higher onan LTE 2100 or LTE 1900 compared to an LTE 700 cells/layers belonging tothe same site or neighboring sites. In this regard Multi-Layer ServiceTriggered Mobility (MLSTM) feature can be used by the optimizationmanager 308 to configure different threshold offset values for variousparameters for different cell sites.

A first set of criteria to determine whether MLSTM should be used mayinclude determining whether layer LTE 2100 MHz or LTE 1900 MHz areco-located with LTE 700 MHz cell sites. More particularly, if LTE 2100VoLTE DCR is greater than LTE 700 and at least a predetermine number ofcalls (e.g., 50) are on LTE 2100; or LTE 1900 VoLTE DCR is greater thanLTE 700 VoLTE DCR and at least a predetermined number of calls (e.g.,50) are on LTE 1900, then MLSTM is applied. More particularly, if thefirst set of criteria are met, the quality of service class identifierQCI parameter “bad coverage” trigger offset parameter(qciA1A2ThrOffsetsqci1.a1a2ThrRsrpQciOffset) is changed to a firstpredetermined value X on LTE 2100 or LTE 1900 cells, accordingly, to addoffset from a present serving layer to a co-site LTE 700 betterperforming layer, and trigger an earlier mobility to shift voice callsto a better performing layer and improve retain-ability.

A second set of criteria to determine whether MLSTM should be used maybe based on VoLTE DCR being higher on the LTE 700 layer in comparison tothe LTE 2100 or LTE 1900 neighbors. More particularly, the second set ofcriteria may include determining that the VoLTE DCR for the LTE 700layer is greater than an average VoLTE DCR of the top predeterminednumber N of LTE 2100 or LTE 1900 neighbors. For example, the top N LTE2100 or L1900 neighbors may be selected based on the highest number ofinter frequency handover attempts. The top neighbor relations aredetermined by the number N. For example, if N=5, then the top five mostfrequently used neighbors are used to calculate the average VoLTE DCR.

Upon determining that the second set of criteria are met, the QCI Level“bad coverage” trigger offset parameter(qciA1A2ThrOffsetsqci1.a1a2ThrRsrpQciOffset) is changed to apredetermine value Y on the LTE 700 cell sites to add an offset from thepresent serving layer towards the LTE 2100 or LTE 1900 layer, andtrigger an earlier mobility to shift voice calls to the betterperforming layer and improve retain-ability. Rows 600N and 6000 of thetable of FIG. 6C provide a summary of relevant KPI's and exampleparameter adjustments performed during an MLSTM based on thecorresponding criteria that are satisfied.

At block 546, the performance of the cell that has been optimized ismonitored. For example, the data acquisition module 312 of thecontroller 200 may receive new data 304 from various sources, such asfrom inputs 302 and the data server 112, to obtain the latest KPI'stherefrom that are related to the subject cell site. The new data 304can be used to compare the new performance of the cell site to thebaseline performance, thereby determining (i.e., at block 550) whetherthe optimization is successfully realized (e.g., determining whether theadjusted performance of the cell site is within a baseline performancerange of the wireless telecommunication network 100 that was calculatedpreviously at block 504).

Upon determining that the desired optimization is achieved (i.e., “YES”at decision block 550), the optimization manager 308 concludes that thesubject cell site is within predetermined one or more ranges of thebaseline previously calculated in block 504. The process then loops backto block 502 to receive network data, after a waiting period (i.e.,block 552), thereby restarting the process. The wait period 552 may havethe same the same considerations as the wait period 522, discussedpreviously.

Upon determining that the desired optimization is not achieved (i.e.,“NO” at decision block 550), the process continues to block 536. Theiterative process continues until the desired optimization is achieved(i.e., the monitored performance at block 546 indicates that the KPI'sof the subject cell site are within a predetermined ranges of thebaseline calculated previously in block 504).

CONCLUSION

While the foregoing has described what are considered to be the bestmode and/or other examples, it is understood that various modificationsmay be made therein and that the subject matter disclosed herein may beimplemented in various forms and examples, and that the teachings may beapplied in numerous applications, only some of which have been describedherein. It is intended by the following claims to claim any and allapplications, modifications and variations that fall within the truescope of the present teachings.

It is understood that any specific order or hierarchy of steps in theprocess disclosed in FIGS. 4 and 5 are illustrations of exemplaryapproaches. Based upon design preferences, it is understood that thespecific order or hierarchy of blocks in the processes may berearranged, expanded, and some steps omitted. Some of the blocks may beperformed simultaneously. For example, the action of load balancing andoptimization of cellular coverage of FIG. 5 may occur concurrently ormay be omitted.

Except as stated immediately above, nothing that has been stated orillustrated is intended or should be interpreted to cause a dedicationof any component, step, feature, object, benefit, advantage, orequivalent to the public, regardless of whether it is or is not recitedin the claims.

It will be understood that the terms and expressions used herein havethe ordinary meaning as is accorded to such terms and expressions withrespect to their corresponding respective areas of inquiry and studyexcept where specific meanings have otherwise been set forth herein.Relational terms such as first and second and the like may be usedsolely to distinguish one entity or action from another withoutnecessarily requiring or implying any actual such relationship or orderbetween such entities or actions. The terms “comprises,” “comprising,”or any other variation thereof, are intended to cover a non-exclusiveinclusion, such that a process, method, article, or apparatus thatcomprises a list of elements does not include only those elements butmay include other elements not expressly listed or inherent to suchprocess, method, article, or apparatus. An element proceeded by “a” or“an” does not, without further constraints, preclude the existence ofadditional identical elements in the process, method, article, orapparatus that comprises the element.

The claims, description, and drawings of this application may describeone or more of the instant technologies in operational/functionallanguage, for example as a set of operations to be performed by acomputer. Such operational/functional description in most instances canbe specifically-configured hardware (e.g., because a general purposecomputer in effect becomes a special purpose computer once it isprogrammed to perform particular functions pursuant to instructions fromprogram software).

Although the operational/functional descriptions described herein areunderstandable by the human mind, they are not abstract ideas of theoperations/functions divorced from computational implementation of thoseoperations/functions. Rather, the operations/functions represent aspecification for the massively complex computational machines or othermeans. As discussed in detail below, the operational/functional languageis to be read in its proper technological context, i.e., as concretespecifications for physical implementations.

The Abstract of the Disclosure is provided to allow the reader toquickly ascertain the nature of the technical disclosure. It issubmitted with the understanding that it will not be used to interpretor limit the scope or meaning of the claims. In addition, in theforegoing Detailed Description, it can be seen that various features aregrouped together in various embodiments for the purpose of streamliningthe disclosure. This method of disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter lies in less than allfeatures of a single disclosed embodiment. Thus the following claims arehereby incorporated into the Detailed Description, with each claimstanding on its own as a separately claimed subject matter.

1. A computing device configured to administer a wirelesstelecommunication network (WTN) having a plurality of cell sites, thecomputing device comprising: a processor; a network interfacecommunicatively coupled to the processor and configured to enablecommunications with the WTN; a storage device coupled to the processor;an application stored in the storage device, wherein execution of theapplication by the processor configures the computing device to performacts comprising: receiving network data from a data source for a subjectcell site of the plurality of cell sites; determining a baselineperformance of the subject cell site based on the received network data;identifying parameters to optimize for the subject cell site based onthe baseline performance; performing load balancing on the subject cellsite by comparing a normalized user equipment (UE) downlink (DL)throughput at a first cellular frequency band to a second cellularfrequency band; adjusting a cellular coverage of the subject cell sitebased at least on a voice over LTE (VoLTE) drop call rate for apredetermined time period and a normalized UE DL throughput; andperforming cellular frequency band management on the subject cell sitebased at least on drop call rates, comprising: 1) determining whetherthe subject cell site meets a set of criteria, the set of criteriacomprising: i) a third cellular frequency band of the subject cell sitehas a VoLTE drop call rate greater than a predetermined percentage valuefor the predetermined time period; ii) a drop call rate of a fourthcellular frequency band of the subject cell site has a VoLTE drop callrate less than a second predetermined percentage value for thepredetermined time period; iii) the third cellular frequency band has atleast a third predetermined number of VoLTE voice calls for thepredetermined time period; iv) a coverage indicator of the thirdcellular frequency band is greater than a fourth predetermined value forthe predetermined time period; v) a coverage indicator of the fourthcellular frequency band is less than a fifth predetermined value for thepredetermined time period; and vi) an average Received Signal Level(RSRP) of the third cellular frequency band is a sixth predeterminedvalue weaker than an RSRP of the fourth cellular frequency band for thepredetermined time period; and 2) upon determining that the subject cellsite meets the set of criteria, moving a call session from the thirdcellular frequency band to the fourth cellular frequency band. 2.(canceled)
 3. The computing device of claim 1, wherein receiving networkdata from a data source comprises receiving historical data for apredetermined time period and new data related to a cell site of thewireless telecommunication network.
 4. The computing device of claim 1,wherein determining the baseline performance of the subject cell sitecomprises: extracting key performance indicators (KPI's) of the subjectcell site over a predetermined time period; and determining an averagevalue for each KPI for the predetermined time period.
 5. The computingdevice of claim 1, wherein determining the baseline performance of thesubject cell site comprises: extracting key performance indicators(KPIs) of other cell sites of the plurality of cell sites; anddetermining an average value for each KPI based on the plurality of cellsites.
 6. The computing device of claim 1, wherein execution of theprogram further configures the computing device to, upon determiningthat one or more other cell sites from the plurality of cell sites havesubstantially similar key performance (KPI) values that exceed thebaseline performance: including the subject cell site and the one ormore other cell sites in a cluster; and applying all acts that areperformed on the subject cell site also on the one or more other cellsites in the cluster.
 7. The computing device of claim 1, whereinperforming load balancing on the subject cell site comprises switching atraffic from the first cellular frequency band to the second cellularfrequency band of the WTN, upon determining that the second cellularfrequency band has a higher throughput.
 8. The computing device of claim1, wherein identifying parameters to optimize for the subject cell sitebased on the baseline performance comprises: comparing each KPI to itscorresponding baseline KPI; and upon determining that a KPI exceeds itscorresponding baseline KPI by a predetermined threshold, identifying thesubject cell site to be non-compliant.
 9. The computing device of claim1, wherein adjusting the cellular coverage on the subject cell sitecomprises: determining whether the subject cell site meets a set ofcriteria, comprising: (i) a drop call rate that is below a predeterminedthreshold percentage in a first time period; (ii) at least a secondpredetermined number of VoLTE voice calls in the first time period;(iii) a data rate that is higher than a third predetermined value in thefirst time period; and (iv) a percentage of calls that are leakingtowards a Universal Mobile Telecommunications System (UMTS) that ishigher than a fourth number in the first time period; and upondetermining that the set of criteria are met, delaying a sessioncontinuity and handover (HO) trigger point from long term evolution(LTE) to UMTS.
 10. The computing device of claim 1, wherein execution ofthe application by the processor further configures the computing deviceto perform acts comprising: identifying an optimization objective forthe subject cell site and only performing the acts of the loadbalancing, adjusting the cellular coverage, and the cellular frequencyband management on the subject cell site, upon identifying that theoptimization objective is an LTE network layer management and not an LTEnetwork coverage and performance optimization.
 11. The computing deviceof claim 1, wherein execution of the application by the processorfurther configures the computing device to perform acts comprising:receiving new network data from the data source for the subject cellsite; comparing a new performance of the subject cell site based on thenew network data to the baseline performance of the subject cell site;upon determining that the new performance of the subject cell site iswithin the baseline performance of the subject cell site, returning tothe act of receiving network data from the data source for the subjectcell site after a predetermined period; and upon determining that thenew performance of the subject cell site is not within the baselineperformance of the subject cell site, iteratively repeating the acts ofperforming the load balancing, adjusting the cellular coverage andperforming the cellular frequency band management on the subject cellsite.
 12. A non-transitory computer-readable medium having storedthereon a plurality of sequences of instructions which, when executed bya processor, cause the processor to perform a method of administering awireless telecommunication network (WTN) having a plurality of cellsites, the method comprising: receiving network data from a data sourcefor a subject cell site of the plurality of cell sites; determining abaseline performance of the subject cell site based on the receivednetwork data; identifying parameters to optimize for the subject cellsite based on the baseline performance; performing load balancing on thesubject cell site by comparing a normalized user equipment (UE) downlink(DL) throughput at a first cellular frequency band to a second cellularfrequency band; adjusting a cellular coverage of the subject cell sitebased at least on a voice over LTE (VoLTE) drop call rate for apredetermined time period and a normalized UE DL throughput; andperforming cellular frequency band management on the subject cell sitebased at least on drop call rates, comprising: 1) determining whetherthe subject cell site meets a set of criteria, the set of criteriacomprising: i) a third cellular frequency band of the subject cell sitehas a VoLTE drop call rate greater than a predetermined percentage valuefor the predetermined time period; ii) a drop call rate of a fourthcellular frequency band of the subject cell site has a VoLTE drop callrate less than a second predetermined percentage value for thepredetermined time period; iii) the third cellular frequency band has atleast a third predetermined number of VoLTE voice calls for thepredetermined time period; iv) a coverage indicator of the thirdcellular frequency band is greater than a fourth predetermined value forthe predetermined time period; v) a coverage indicator of the fourthcellular frequency band is less than a fifth predetermined value for thepredetermined time period; and vi) an average Received Signal Level(RSRP) of the third cellular frequency band is a sixth predeterminedvalue weaker than an RSRP of the fourth cellular frequency band for thepredetermined time period; and 2) upon determining that the subject cellsite meets the set of criteria, moving a call session from the thirdcellular frequency band to the fourth cellular frequency band. 13.(canceled)
 14. The medium of claim 0, wherein receiving network datafrom a data source comprises receiving historical data for apredetermined time period and new data related to a cell site of thewireless telecommunication network.
 15. The medium of claim 0, whereindetermining the baseline performance of the subject cell site comprises:extracting key performance indicators (KPI's) of the subject cell siteover a predetermined time period; and determining an average value foreach KPI for the predetermined time period.
 16. The medium of claim 0,wherein determining the baseline performance of the subject cell sitecomprises: extracting key performance indicators (KPIs) of other cellsites of the plurality of cell sites; and determining an average valuefor each KPI based on the plurality of cell sites.
 17. The medium ofclaim 0, further comprising, upon determining that one or more othercell sites from the plurality of cell sites have substantially similarkey performance (KPI) values that exceed the baseline performance:including the subject cell site and the one or more other cell sites ina cluster; and applying all acts that are performed on the subject cellsite also on the one or more other cell sites in the cluster.
 18. Themedium of claim 0, wherein performing load balancing on the subject cellsite comprises switching a traffic from the first cellular frequencyband to the second cellular frequency band of the WTN, upon determiningthat the second cellular frequency band has a higher throughput.
 19. Themedium of claim 0, wherein identifying parameters to optimize for thesubject cell site based on the baseline performance comprises: comparingeach KPI to its corresponding baseline KPI; and upon determining that aKPI exceeds its corresponding baseline KPI by a predetermined threshold,identifying the subject cell site to be non-compliant.
 20. The medium ofclaim 0, wherein adjusting the cellular coverage on the subject cellsite comprises: determining whether the subject cell site meets a set ofcriteria, comprising: (i) a drop call rate that is below a predeterminedthreshold percentage in a first time period; (ii) at least a secondpredetermined number of VoLTE voice calls in the first time period;(iii) a data rate that is higher than a third predetermined value in thefirst time period; and (iv) a percentage of calls that are leakingtowards a Universal Mobile Telecommunications System (UMTS) that ishigher than a fourth number in the first time period; and upondetermining that the set of criteria are met, delaying a sessioncontinuity and handover (HO) trigger point from long term evolution(LTE) to UMTS.
 21. The medium of claim 0, the method further comprising:receiving new network data from the data source for the subject cellsite; comparing a new performance of the subject cell site based on thenew network data to the baseline performance of the subject cell site;upon determining that the new performance of the subject cell site iswithin the baseline performance of the subject cell site, returning tothe act of receiving network data from the data source for the subjectcell site after a predetermined period; and upon determining that thenew performance of the subject cell site is not within the baselineperformance of the subject cell site, iteratively repeating the acts ofperforming the load balancing, adjusting the cellular coverage andperforming the cellular frequency band management on the subject cellsite.